On non-elitist evolutionary algorithms optimizing fitness functions with a plateau
AV Eremeev - … Conference on Mathematical Optimization Theory and …, 2020 - Springer
International Conference on Mathematical Optimization Theory and Operations …, 2020•Springer
We consider the expected runtime of non-elitist evolutionary algorithms (EAs), when they are
applied to a family of fitness functions Plateau _r with a plateau of second-best fitness in a
Hamming ball of radius r around a unique global optimum. On one hand, using the level-
based theorems, we obtain polynomial upper bounds on the expected runtime for some
modes of non-elitist EA based on unbiased mutation and the bitwise mutation in particular.
On the other hand, we show that the EA with fitness proportionate selection is inefficient if …
applied to a family of fitness functions Plateau _r with a plateau of second-best fitness in a
Hamming ball of radius r around a unique global optimum. On one hand, using the level-
based theorems, we obtain polynomial upper bounds on the expected runtime for some
modes of non-elitist EA based on unbiased mutation and the bitwise mutation in particular.
On the other hand, we show that the EA with fitness proportionate selection is inefficient if …
Abstract
We consider the expected runtime of non-elitist evolutionary algorithms (EAs), when they are applied to a family of fitness functions with a plateau of second-best fitness in a Hamming ball of radius r around a unique global optimum. On one hand, using the level-based theorems, we obtain polynomial upper bounds on the expected runtime for some modes of non-elitist EA based on unbiased mutation and the bitwise mutation in particular. On the other hand, we show that the EA with fitness proportionate selection is inefficient if the bitwise mutation is used with the standard settings of mutation probability.
Springer
Showing the best result for this search. See all results